1. Field of the Invention
This invention relates in general to the fields of bioengineering and computer technology, and more particularly to a novel brain-computer interface and related methods involving generating electrical outputs from raw brain signals.
2. Description of the Related Art
Brain-computer interfaces (BCI) are systems that provide communications between human beings and machines. BCI's can be used, for example, by individuals to control an external device such as a wheelchair. A major goal of brain-computer interfaces (BCI) is to decode intent from the brain activity of an individual, and signals representing the decoded intent are then used in various ways to communicate with an external device. BCI's hold particular promise for aiding people with severe motor impairments.
Several signal acquisition modalities are currently used for BCI operation in human and non-human primates. These include electroencephalographic signals (EEG) acquired from scalp electrodes, and single neuron activity assessed by microelectrodes arrays or glass cone electrodes. EEG is considered a safe and non-invasive modality, but has low spatial resolution and a poor signal to noise ratio due to signal attenuation by the skull, and signal contamination from muscle activity. In contrast, single-unit recordings of the signals from an individual neuron convey a significantly finer spatial resolution with higher information transfer rates and enable the use of more independent channels. However, single unit recordings require close proximity (within 100 microns) with neurons and therefore are not generally suitable for human applications because of the much higher associated clinical risk, and the lack of durable effect secondary to scar formation around the electrodes.
BCI systems that have achieved closed loop, continuous, and real time control in human subjects are known and typically utilize EEG signal. Most closed loop trials using such systems have utilized low frequency band power changes associated with sensorimotor cortex, known as the mu and beta rhythms. The mu and beta rhythms are thought to be the product of thalamocortical circuits that show suppressed frequency power on cortical activation. These power suppressions, also known as Event Related Descynchronizations (ERD), can be induced by both actual and imagined motor movements. The mu rhythms (8–12 Hz) and beta rhythms (18–26 Hz) are separable in regards to timing and topographical distribution, but tend to show diffuse bilateral (contralateral dominant) suppression with a given motor activity. Additionally, more regionally specific higher frequency bands, known as gamma rhythms, have also been investigated. The gamma band (>30 Hz) is often associated with an increased power (Event Related Synchronization—ERS) in association with cortical activation and has been postulated to be associated with motor programming, attention, and sensorimotor integration. These higher frequency oscillations have not been utilized in a BCI system.
U.S. Pat. No. 5,638,826 (Wolpaw) describes a BCI system using electroencephalographic signal (EEG) in which mu rhythm suppressions (8–12 Hz) are utilized.
U.S. Pat. No. 6,349,231 describes a hybrid BCI based on EEG brain waves in combination with the biopotentials produced by muscles, heart rate, eye movements, and eye blinks.
However, known BCI systems remain limited by the constraints on spatial resolution and signal strength imposed by the chosen signaling modality, such as the constraints imposed by using EEG. Therefore, a need remains for improved BCI systems that are more readily adaptable to human clinical applications.